The origin of bursts and heavy tails in human dynamics

TL;DR

This paper explains that the bursty and heavy-tailed patterns in human activity timing are due to priority-based decision processes, contrasting with random Poisson models, with implications for resource management.

Contribution

It introduces a queuing model based on task priority to explain the heavy-tailed distribution of human activity timings, challenging previous Poisson assumptions.

Findings

Bursty human activity results from priority-based task execution.

Priority blind execution leads to uniform interevent times.

Implications for optimizing resource and service management.

Abstract

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. Here we show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experience very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. These findings have important implications from resource management to service allocation in both communications and retail.